We have checked our distribution by showing it as a *distplot*, a *qqplot*, and by performing a *normaltest*. Let's compare normal plots and what we received to decide what distribution we have.

> From the previous chapter, we learned that if the normaltest shows the value > 0.05, the distribution is normal.

As we have a normal distribution, our criterion will be a **t-criterion** (**Student's criterion**).

A/B test is one of the critical decisions when implementing something new in the IT sphere. It is the right time to get acquainted with this test!

In this section, we will learn some preparation things that are held before the A/B test.

In this section, we will perform our first A/B test. An easy version of the A/B test will help us to practice without difficulties!

It is time to meet the real A/B test. In this section, we will train ourselves using the knowledge we received during the two previous sections. After studying this section, you can say: 'I know what the A/B test is!'.

A/B Testing in Python

Criterion